1. Field of the Invention
The present invention relates to a device for reducing noise included in a video signal, and more specifically, to a noise reducer capable of reducing noise effectively by controlling parameters for noise reduction.
2. Description of the Related Art
With the recent progress in the field of semiconductor memories, inexpensive frame memories have become available. Using such frame memories, three-dimensional processing of video signals has been realized in various applications. As for noise reducers for home VTRs and TV receivers, many types using frame memories have been proposed. As one of such noise reducers, a frame recursive type noise reducer employing Hadamard transformation, which uses an orthogonal transformation, has been proposed, where the difference in the three-dimensional statistical characteristic between a video signal and random noise is utilized (The Journal of the Institute of Television Engineers of JAPAN, Vol. 37, No. 12, 1983, pp. 56-62).
A video signal without noise has large correlations in all of the horizontal, vertical, and temporal directions, while random noise has little correlation in any of the three directions. The noise reducer employing the Hadamard transformation utilizes this difference in the three-dimensional correlations between a video signal and random noise more effectively to reduce noise. The frame recursive type noise reducer employing the Hadamard transformation is advantageous over a simple frame recursive type noise reducer without using the Hadamard transformation in that the resolution of the motion picture portion of the transmission is less deteriorated under the condition where the improvement in the S/N ratio is the same.
A conventional frame recursive type noise reducer employing the Hadamard transformation will be described with reference to FIG. 48. A noise reducer 900 includes a noise extract portion 9 which extracts noise included in an input video signal S1, and a second subtracter 8 which subtracts an extracted noise signal S2 from the input video signal S1, so as to obtain an output signal S3 with reduced noise.
Referring to FIG. 48, the noise extract portion 9 includes a first subtracter 1, a frame memory 2, a serial/parallel converter 3, an Hadamard transformer 4, nonlinear processing portions 5-1 to 5-k (hereinafter, collectively referred to as a nonlinear processor 5, to avoid causing misunderstanding), an Hadamard inverse transformer 6, and parallel/serial converter 7. The frame memory 2 receives the output signal S3 with reduced noise obtained by subtracting the noise signal S2 extracted in the noise extract portion 9 from the input video signal S1 as described above, and outputs a delayed signal S4 by delaying the output signal S3 by one frame or several frames. The first subtracter 1 subtracts the delayed signal S4 from the input video signal S1 so as to obtain a frame differential signal S5. The serial/parallel converter 3 converts a temporally serial data series (S5) into a temporally parallel data series P1 corresponding to the order of the Hadamard transformation. The Hadamard transformer 4 conducts the Hadamard transformation on the parallel data series P1 so as to obtain a data series P2. The nonlinear processor 5 conducts nonlinear processing on the Hadamard-transformed data series P2 so as to obtain data P3. The Hadamard inverse transformer 6 conducts an Hadamard inverse transformation, i.e., an operation inverse to that conducted by the Hadamard transformer 4, on the data P3 so as to obtain a parallel data series P4. The parallel/serial converter 7 converts the parallel data series P4 into a serial data series. The output from the parallel/serial converter 7 is the extracted noise signal S2 output from the noise extract portion 9. The second subtracter 8 subtracts the noise signal S2 from the input video signal S1, so as to obtain the output signal S3 with reduced noise.
The operation of the noise reducer 900 with the above configuration will be described in detail.
First, the first subtracter 1 calculates the difference between the input video signal S1 and the delayed signal S4 with reduced noise delayed by N frame(s) (N=1, 2, . . . ) by the frame memory 2. Since random noise and a motion component included in the video signal have small correlation in the temporal direction, they are extracted by this differential operation and are output as the frame differential signal S5 corresponding to the amplitude of the noise and the motion component. The serial/parallel converter 3 converts the temporally serial frame differential data (S5) into the temporally parallel data series P1 composed of m sample points in the horizontal direction and n lines in the vertical direction (m, n=natural numbers). The serial/parallel converter 3 includes n-1 line memory or memories and (m-1).times.n latch or latches.
Hereinbelow, the case where one pixel block is composed of m=4 samples in the horizontal direction and n=2 lines in the vertical direction will be described. A temporally parallel block (a pixel block composed of temporally parallel data) produced by the serial/parallel converter 3 is expressed in the form of matrix by formula (1): ##EQU1##
The block data composed of x.sub.00 to x.sub.03 and x.sub.10 to x.sub.13 will be described. When x.sub.00 is considered as the reference, x.sub.01, x.sub.02, and x.sub.03 are data located right of the reference by one sample, two samples, and three samples, respectively. Likewise, when x.sub.10 is considered as the reference, x.sub.11, x.sub.12, and x.sub.13 are data located right of the reference by one sample, two samples, and three samples, respectively. The data x.sub.10 to x.sub.13 are located below the data x.sub.00 to x.sub.03 by one line.
The Hadamard transformer 4 conducts the Hadamard transformation expressed by formula (2) below on the temporally parallel block data of four samples in the horizontal direction and two lines in the vertical direction, so as to obtain 4 (samples).times.2 (lines)=8 frequency components in the Hadamard space. ##EQU2## wherein y.sub.ij (0.ltoreq.i.ltoreq.1, 0.ltoreq.j.ltoreq.3) represents the Hadamard-transformed data.
Since random noise has less correlation among data, it is uniformly distributed to the respective frequency components y.sub.ij in the Hadamard space expressed by formula (2). The absolute value of each frequency component y.sub.ij is input into the nonlinear processor 5, which then extracts noise uniformly distributed to the respective frequency components y.sub.ij. The relationship between the input and output of the nonlinear processor 5 is shown in FIG. 49, where the X-axis represents the input and the Y-axis represents the output. As is observed from FIG. 49, when the frequency component y.sub.ij whose absolute value is equal to or more than a predetermined threshold A is input, the output is zero.
Thereafter, the noise component extracted by the nonlinear processor 5 is inverse-operated as expressed by formula (3) below by the Hadamard inverse transformer 6, so as to return the data to the component in real space. ##EQU3## wherein x'.sub.ij represents each component of the noise signal returned to the real space.
The noise component x'.sub.ij is then converted into the temporally serial noise signal S2 by the parallel/serial converter 7. Thereafter, the second subtracter 8 subtracts the noise signal S2 from the input video signal S1 including noise. Thus, the noise is reduced by the conventional noise reducer 900.
In the conventional noise reducer 900, the threshold A for the input/output characteristic of the nonlinear processor 5 is fixed to a predetermined value as shown in FIG. 49. Accordingly, when the absolute value of a motion component included in the input video signal S1 is comparatively small, i.e., equal to or less than the threshold A, the nonlinear processor 5 extracts the motion component as noise, causing a phenomenon such as lag and trailing on the moving picture displayed. On the contrary, when the amplitude of noise is considerably large, since the portion of such noise of which absolute value exceeds the threshold A is not extracted, the noise signal S2 returned from the nonlinear processor 5 is smaller than the original noise included in the input video signal S1. As a result, a sufficient noise reduction effect is not obtained. Further, when the input video signal S1 includes little noise or the noise has a small amplitude, the motion component of the video signal is extracted and subtracted from the input video signal and this results in causing a phenomenon such as lag and trailing in the displayed motion picture more prominent because the influence of the noise itself is smaller.